Evaluate The Results

Lesson 2 of 8

Now let’s evaluate the quality of the model by having it generate predictions (called scoring) for the remaining 20% of data in the test partition. Then we’ll compare those predictions to the actual median house values, and calculate the regression evaluation metrics.

So imagine you are a realtor in California selling houses. What kind of prediction accuracy would you consider acceptable?

...

Please provide your access code to unlock and read the remainder of this lesson. Your code will be securely stored in your browser, so you only need to enter it once. If you do not have an access code for this lab, subscribe to all-access membership or buy the course to get your code.

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
Previous Lesson Next Lesson